Mental Representation Impact Analysis (MERIA), a method for analyzing mental representations for the design of HMI. A case study in aeronautics

Airline pilots in civil aviation operate in dynamic and uncertain situations, supported by complex technical systems. In these environments, risk management by front-line operators must be continuously minimized and controlled, and pilots are subject to high cognitive loads, which can lead to some piloting errors. To facilitate the activity, cockpit and interface designers are seeking to optimize pilot situational awareness and mental representation. In this study, we are interested in the mental representations of co-pilots when performing in risky scenarios. In particular, we studied the gaps between the “prescribed, expected” and “real, effective” mental representation of co-pilots, highlighting the artifacts that are at the root of these gaps. To understand the evolution of mental representation over the course of an activity, we submitted a cohort of co-pilots to the experience of a risky scenario. Their activity was filmed, commented on by experts, and then self-confrontation interviews were conducted to gather the different points of view of the activity. Through the presentation of a case study of a co-pilot, this article describes our original tool for graphical and chronological representation of the activity. This tool highlights: the mental representations of the co-pilot at each stage of the scenario, the gaps that may or may not have impacted the activity, the use of available technology and the impact that this may have had on the mental representations. This tool has many advantages: an efficient comparison of mental states of two or more operators, an almost exhaustive presentation of the many datasets collected and analyzed, a synthetic and precise vision of the activity. The analysis tool is applicable to fields other than aeronautics and offers considerable opportunities to identify errors of cognitive origin and solve them at the source.